Exploring Indoor Localization for Smart Education
This comprehensive study delves into the realm of indoor positioning technologies within the domain of Smart Education (SE). Focusing on typical techniques and technologies in educational settings, the research emphasizes the importance and potential services of localization in SE. Moreover, this work explores the feasibility and limitations of these technologies, providing a detailed account of their role in educational settings. The paper also contains in an innovative Proof of Concept (PoC), demonstrating an automatic attendance control (AAC) system that integrates 5G and WiFi technologies. This PoC effectively showcases the possibilities and effectiveness of location-based services in educational surroundings even with a limited budget, setting the stage for optimizing teaching time, enhancing the quality of education.
Code (0)
등록된 구현이 없습니다.
Tasks
Indoor LocalizationSimilar Papers 제목 키워드 기반
Multi-Head Attention Neural Network for Smartphone Invariant Indoor Localization
Smartphones together with RSSI fingerprinting serve as an efficient approach for delivering a low-cost and high-accuracy indoor localization solution. However, a few critical challenges have prevented the wide-spread pro…
Indoor LocalizationSmartphone region-wise image indoor localization using deep learning for indoor tourist attraction
Smart indoor tourist attractions, such as smart museums and aquariums, usually require a significant investment in indoor localization devices. The smartphone Global Positional Systems use is unsuitable for scenarios whe…
Indoor LocalizationQuickLoc: Adaptive Deep-Learning for Fast Indoor Localization with Mobile Devices
Indoor localization services are a crucial aspect for the realization of smart cyber-physical systems within cities of the future. Such services are poised to reinvent the process of navigation and tracking of people and…
Deep LearningIndoor LocalizationVision-Based Localization and LLM-based Navigation for Indoor Environments
Indoor navigation remains a complex challenge due to the absence of reliable GPS signals and the architectural intricacies of large enclosed environments. This study presents an indoor localization and navigation approac…
Indoor Smartphone SLAM with Learned Echoic Location Features
Indoor self-localization is a highly demanded system function for smartphones. The current solutions based on inertial, radio frequency, and geomagnetic sensing may have degraded performance when their limiting factors t…
Contrastive LearningSimultaneous Localization and Mapping